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* AI sidebar * Add chat and message models with associations * Implement AI chat functionality with sidebar and messaging system - Add chat and messages controllers - Create chat and message views - Implement chat-related routes - Add message broadcasting and user interactions - Update application layout to support chat sidebar - Enhance user model with initials method * Refactor AI sidebar with enhanced chat menu and interactions - Update sidebar layout with dynamic width and improved responsiveness - Add new chat menu Stimulus controller for toggling between chat and chat list views - Improve chat list display with recent chats and empty state - Extract AI avatar to a partial for reusability - Enhance message display and interaction styling - Add more contextual buttons and interaction hints * Improve chat scroll behavior and message styling - Refactor chat scroll functionality with Stimulus controller - Optimize message scrolling in chat views - Update message styling for better visual hierarchy - Enhance chat container layout with flex and auto-scroll - Simplify message rendering across different chat views * Extract AI avatar to a shared partial for consistent styling - Refactor AI avatar rendering across chat views - Replace hardcoded avatar markup with a reusable partial - Simplify avatar display in chats and messages views * Update sidebar controller to handle right panel width dynamically - Add conditional width class for right sidebar panel - Ensure consistent sidebar toggle behavior for both left and right panels - Use specific width class for right panel (w-[375px]) * Refactor chat form and AI greeting with flexible partials - Extract message form to a reusable partial with dynamic context support - Create flexible AI greeting partial for consistent welcome messages - Simplify chat and sidebar views by leveraging new partials - Add support for different form scenarios (chat, new chat, sidebar) - Improve code modularity and reduce duplication * Add chat clearing functionality with dynamic menu options - Implement clear chat action in ChatsController - Add clear chat route to support clearing messages - Update AI sidebar with dropdown menu for chat actions - Preserve system message when clearing chat - Enhance chat interaction with new menu options * Add frontmatter to project structure documentation - Create initial frontmatter for structure.mdc file - Include description and configuration options - Prepare for potential dynamic documentation rendering * Update general project rules with additional guidelines - Add rule for using `Current.family` instead of `current_family` - Include new guidelines for testing, API routes, and solution approach - Expand project-specific rules for more consistent development practices * Add OpenAI gem and AI-friendly data representations - Add `ruby-openai` gem for AI integration - Implement `to_ai_readable_hash` methods in BalanceSheet and IncomeStatement - Include Promptable module in both models - Add savings rate calculation method in IncomeStatement - Prepare financial models for AI-powered insights and interactions * Enhance AI Financial Assistant with Advanced Querying and Debugging Capabilities - Implement comprehensive AI financial query system with function-based interactions - Add detailed debug logging for AI responses and function calls - Extend BalanceSheet and IncomeStatement models with AI-friendly methods - Create robust error handling and fallback mechanisms for AI queries - Update chat and message views to support debug mode and enhanced rendering - Add AI query routes and initial test coverage for financial assistant * Refactor AI sidebar and chat layout with improved structure and comments - Remove inline AI chat from application layout - Enhance AI sidebar with more semantic HTML structure - Add descriptive comments to clarify different sections of chat view - Improve flex layout and scrolling behavior in chat messages container - Optimize message rendering with more explicit class names and structure * Add Markdown rendering support for AI chat messages - Implement `markdown` helper method in ApplicationHelper using Redcarpet - Update message view to render AI messages with Markdown formatting - Add comprehensive Markdown rendering options (tables, code blocks, links) - Enhance AI Financial Assistant prompt to encourage Markdown usage - Remove commented Markdown CSS in Tailwind application stylesheet * Missing comma * Enhance AI response processing with chat history context * Improve AI debug logging with payload size limits and internal message flag * Enhance AI chat interaction with improved thinking indicator and scrolling behavior * Add AI consent and enable/disable functionality for AI chat * Upgrade Biome and refactor JavaScript template literals - Update @biomejs/biome to latest version with caret (^) notation - Refactor AI query and chat controllers to use template literals - Standardize npm scripts formatting in package.json * Add beta testing usage note to AI consent modal * Update test fixtures and configurations for AI chat functionality - Add family association to chat fixtures and tests - Set consistent password digest for test users - Enable AI for test users - Add OpenAI access token for test environment - Update chat and user model tests to include family context * Simplify data model and get tests passing * Remove structure.mdc from version control * Integrate AI chat styles into existing prose pattern * Match Figma design spec, implement Turbo frames and actions for chats controller * AI rules refresh * Consolidate Stimulus controllers, thinking state, controllers, and views * Naming, domain alignment * Reset migrations * Improve data model to support tool calls and message types * Tool calling tests and fixtures * Tool call implementation and test * Get assistant test working again * Test updates * Process tool calls within provider * Chat UI back to working state again * Remove stale code * Tests passing * Update openai class naming to avoid conflicts * Reconfigure test env * Rebuild gemfile * Fix naming conflicts for ChatResponse * Message styles * Use OpenAI conversation state management * Assistant function base implementation * Add back thinking messages, clean up error handling for chat * Fix sync error when security price has bad data from provider * Add balance sheet function to assistant * Add better function calling error visibility * Add income statement function * Simplify and clean up "thinking" interactions with Turbo frames * Remove stale data definitions from functions * Ensure VCR fixtures working with latest code * basic stream implementation * Get streaming working * Make AI sidebar wider when left sidebar is collapsed * Get tests working with streaming responses * Centralize provider error handling * Provider data boundaries --------- Co-authored-by: Josh Pigford <josh@joshpigford.com>
178 lines
5.6 KiB
Ruby
178 lines
5.6 KiB
Ruby
# Orchestrates LLM interactions for chat conversations by:
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# - Streaming generic provider responses
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# - Persisting messages and tool calls
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# - Broadcasting updates to chat UI
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# - Handling provider errors
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class Assistant
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include Provided
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attr_reader :chat
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class << self
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def for_chat(chat)
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new(chat)
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end
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end
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def initialize(chat)
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@chat = chat
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end
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def streamer(model)
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assistant_message = AssistantMessage.new(
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chat: chat,
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content: "",
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ai_model: model
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)
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proc do |chunk|
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case chunk.type
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when "output_text"
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stop_thinking
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assistant_message.content += chunk.data
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assistant_message.save!
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when "function_request"
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update_thinking("Analyzing your data to assist you with your question...")
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when "response"
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stop_thinking
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assistant_message.ai_model = chunk.data.model
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combined_tool_calls = chunk.data.functions.map do |tc|
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ToolCall::Function.new(
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provider_id: tc.id,
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provider_call_id: tc.call_id,
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function_name: tc.name,
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function_arguments: tc.arguments,
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function_result: tc.result
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)
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end
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assistant_message.tool_calls = combined_tool_calls
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assistant_message.save!
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chat.update!(latest_assistant_response_id: chunk.data.id)
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end
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end
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end
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def respond_to(message)
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chat.clear_error
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sleep artificial_thinking_delay
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provider = get_model_provider(message.ai_model)
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provider.chat_response(
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message,
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instructions: instructions,
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available_functions: functions,
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streamer: streamer(message.ai_model)
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)
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rescue => e
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chat.add_error(e)
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end
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private
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def update_thinking(thought)
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chat.broadcast_update target: "thinking-indicator", partial: "chats/thinking_indicator", locals: { chat: chat, message: thought }
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end
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def stop_thinking
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chat.broadcast_remove target: "thinking-indicator"
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end
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def process_response_artifacts(data)
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messages = data.messages.map do |message|
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AssistantMessage.new(
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chat: chat,
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content: message.content,
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provider_id: message.id,
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ai_model: data.model,
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tool_calls: data.functions.map do |fn|
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ToolCall::Function.new(
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provider_id: fn.id,
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provider_call_id: fn.call_id,
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function_name: fn.name,
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function_arguments: fn.arguments,
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function_result: fn.result
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)
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end
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)
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end
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messages.each(&:save!)
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end
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def instructions
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<<~PROMPT
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## Your identity
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You are a financial assistant for an open source personal finance application called "Maybe", which is short for "Maybe Finance".
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## Your purpose
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You help users understand their financial data by answering questions about their accounts,
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transactions, income, expenses, net worth, and more.
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## Your rules
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Follow all rules below at all times.
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### General rules
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- Provide ONLY the most important numbers and insights
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- Eliminate all unnecessary words and context
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- Ask follow-up questions to keep the conversation going. Help educate the user about their own data and entice them to ask more questions.
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- Do NOT add introductions or conclusions
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- Do NOT apologize or explain limitations
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### Formatting rules
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- Format all responses in markdown
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- Format all monetary values according to the user's preferred currency
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#### User's preferred currency
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Maybe is a multi-currency app where each user has a "preferred currency" setting.
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When no currency is specified, use the user's preferred currency for formatting and displaying monetary values.
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- Symbol: #{preferred_currency.symbol}
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- ISO code: #{preferred_currency.iso_code}
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- Default precision: #{preferred_currency.default_precision}
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- Default format: #{preferred_currency.default_format}
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- Separator: #{preferred_currency.separator}
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- Delimiter: #{preferred_currency.delimiter}
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### Rules about financial advice
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You are NOT a licensed financial advisor and therefore, you should not provide any financial advice. Instead,
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you should focus on educating the user about personal finance and their own data so they can make informed decisions.
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- Do not provide financial and/or investment advice
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- Do not suggest investments or financial products
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- Do not make assumptions about the user's financial situation. Use the functions available to get the data you need.
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### Function calling rules
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- Use the functions available to you to get user financial data and enhance your responses
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- For functions that require dates, use the current date as your reference point: #{Date.current}
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- If you suspect that you do not have enough data to 100% accurately answer, be transparent about it and state exactly what
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the data you're presenting represents and what context it is in (i.e. date range, account, etc.)
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PROMPT
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end
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def functions
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[
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Assistant::Function::GetTransactions.new(chat.user),
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Assistant::Function::GetAccounts.new(chat.user),
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Assistant::Function::GetBalanceSheet.new(chat.user),
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Assistant::Function::GetIncomeStatement.new(chat.user)
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]
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end
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def preferred_currency
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Money::Currency.new(chat.user.family.currency)
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end
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def artificial_thinking_delay
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1
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end
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end
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